Candidate Identification Technique for Lung Cancer

2021 ◽  
Vol 10 (1) ◽  
pp. 1-13
Author(s):  
Sadaf Batool Naqvi ◽  
Abad Ali Shah
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Mortality Rate ◽  
Early Identification ◽  
Research Work ◽  
Cancer Prognosis ◽  
Lung Cancer Patients ◽  
Identification Technique ◽  
Stage 1 ◽  
Candidate Identification

Intensive research work has been done related to lung cancer prognosis. However, the current research mainly emphasises on decreasing the mortality rate, and increasing the survival rate of lung cancer patients. In this paper, the authors argue that an early identification and candidate identification (CI) of this disease can change the early detection treatment of lung cancer and hence can markedly reduce the mortality rate. The proposed technique CI will recognize the disease well in advance and can potentially save the candidate's life. In other words, a candidate of lung cancer is identified and treated in Stage 0 (explained later) instead of in Stage 1 or in the later stages of the lung cancer. In this paper, the authors have introduced a technique, called candidate identification, to identify candidates of the lung cancer. In the proposed technique, a backward forecasting function (BFF) is also proposed to generate Stage 0 data of the patients who have already lung cancer.

Prediction System for the Lung Cancer Patients and Classification Accuracy Enhancement Using Ensemble Method

2021 ◽  
Vol 11 (3) ◽  
pp. 856-862
Author(s):  
R. Kaviarasi ◽  
R. Gandhi Raj
Keyword(s):  
Lung Cancer ◽  
Feature Selection ◽  
Survival Rate ◽  
Cancer Patients ◽  
Classification Accuracy ◽  
Tnm Stage ◽  
Supervised Machine Learning ◽  
Prediction System ◽  
Lung Cancer Patients ◽  
Stage 1

Lung cancer is the biggest challenge in the research world. Blood samples for lung cancer patients are significant for the prediction method in the research environment. Accurate prediction is essential to increase the survival period and may help to take proper medication. The feature selection is an essential part of this prediction system. In this method, the essential features are analyzed from lung cancer patient’s blood. Biomarkers can be identified from blood and other tests. Biomarkers are used in many scientific fields. The Serum CKAP4 levels were analyzed from lung cancer patient’s blood at the TNM stages. White blood counts and Hemoglobin are viewed as an analysis of immunity, and CKAP4 is located at an immunity level that has been recognized in the body fluid of patients with lung cancer. The system is analyzed immunity from collected real health information by a proposed Gaussian Kb Ensemble Weighting Classifier method. The novel attributes are composed of a cancer research center and cancer sanatoriums. The measurement of weighting value {low = 0, high = 1} of blood in Serum CKAP4, Hemoglobin, and the WBC are classified by immunity range. High immunity people’s survival rate is high at TNM stage 1. If not, high immunity was survival rate is low at TNM stage 1. Lung cancer patient’s survivability classification was performed by various supervised machine learning models such as Ada boost, neural networks, and SVM model. The Gaussian Kb Ensemble Weighting Classifier method helped to improve the classification accuracy by feature selection and the algorithm was implemented in the MATLAB environment. Kaplan–Meier curve method used to analyzes results. The classified labels are compared with existing results. The area proved the Gaussian Kb Ensemble weighting classifier algorithm under the Curve through the ROC method.

scholarly journals MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 209
Author(s):  
Davide Marzorati ◽  
Luca Mainardi ◽  
Giulia Sedda ◽  
Roberto Gasparri ◽  
Lorenzo Spaggiari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Mortality Rate ◽  
Early Diagnosis ◽  
Gas Sensor ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.

Long-Term Survival Associated With Complete Resection After Induction Chemotherapy in Stage IIIA (N2) and IIIB (T4N0-1) Non–Small-Cell Lung Cancer Patients: The Spanish Lung Cancer Group Trial 9901

2007 ◽  
Vol 25 (30) ◽  
pp. 4736-4742 ◽  
Author(s):  
Pilar Garrido ◽  
José Luis González-Larriba ◽  
Amelia Insa ◽  
Mariano Provencio ◽  
Antonio Torres ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Cancer Patients ◽  
Induction Chemotherapy ◽  
Complete Resection ◽  
Small Cell ◽  
Stage Iiib ◽  
Small Cell Lung ◽  
Stage Iiia ◽  
Lung Cancer Patients

PurposeTo assess the activity of induction chemotherapy followed by surgery in stage IIIA and selected stage IIIB non–small-cell lung cancer patients.Patients and MethodsMediastinoscopy proof of either positive N2 (IIIA) or T4N0-1 (IIIB) disease was required. Induction therapy was three cycles of cisplatin/gemcitabine/docetaxel, followed by surgery.ResultsFrom December 1999 to March 2003, 136 patients were entered onto the study; the clinical response rate in 129 assessable patients was 56%. The overall complete resection rate was 68.9% of patients eligible for surgery (72% of stage IIIA patients and 66% of stage IIIB patients) and 48% of all assessable patients. Eight (12.9%) of 62 completely resected patients had a pathologic complete response. Seven patients (7.8%) died during the postoperative period. The median overall survival time was 15.9 months, 3-year survival rate was 36.8%, and 5-year survival rate was 21.1%, with no significant differences in survival between stage IIIA and stage IIIB patients. Median survival time was 48.5 months for 62 completely resected patients, 12.9 months for 13 incompletely resected patients, and 16.8 months for 15 nonresected patients (P = .005). Three- and 5-year survival rates were 60.1% and 41.4% for completely resected patients, 23.1% and 11.5% for incompletely resected patients, and 31.1% and 0% for nonresected patients, respectively. In the multivariate analysis, complete resection (hazard ratio [HR] = 0.35; P < .0001), clinical response (HR = 0.32; P < .0001), and age younger than 60 years (HR = 0.64; P = .027) were the most powerful prognostic factors.ConclusionInduction chemotherapy followed by surgery is effective in stage IIIA and in selected stage IIIB patients attaining complete resection.

A New Multiparametric Classification in Lung Cancer Patients - S.M.I.G.

1983 ◽  
Vol 69 (5) ◽  
pp. 437-443 ◽  
Author(s):  
Claudio Modini ◽  
Mario Albertucci ◽  
Franco Cicconetti ◽  
Donatella Tirindelli Danesi ◽  
Renzo Cristiani ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Growth Rate ◽  
Mortality Rate ◽  
Cancer Patients ◽  
Cell Type ◽  
Tnm System ◽  
Lung Cancer Patients ◽  
The Difference

The classification of bronchogenic carcinoma as a function of the prognosis is still an open field. The evaluation of stage, by use of the TNM system, and histologic cell type is not sufficient to guarantee a correct prognosis. The growth rate of the neoplasm is another important parameter. We propose a classification that takes into account the stage (S), histologic cell type (M), immune status (I) and the growth rate of the primary tumor (G): S.M.I.G. We studied 90 lung cancer patients according to the S.M.I.G. classification and we observed that their prognoses were directly correlated with their S.M.I.G. scores (the higher the score, the higher the 10-month mortality rate). The mortality rates within the first 10 months of follow-up were respectively 0%, 0%, 36.36%, 68%, 90.9% for the 5 groups obtained by S.M.I.G. The difference is statistically significant (P < 0.0075) and there is a linear correlation between the mortality rate and the score assigned to each group (R = 0.943; P < 0.05). The S.M.I.G. classification can predict the prognosis more efficiently than the usual classification (TNM) and histological cell type.

scholarly journals In-hospital interstage improves interstage survival after the Norwood stage 1 operation

2020 ◽  
Vol 57 (6) ◽  
pp. 1113-1121
Author(s):  
Guido Michielon ◽  
Giovanni DiSalvo ◽  
Alain Fraisse ◽  
Julene S Carvalho ◽  
Sylvia Krupickova ◽  
...  
Keyword(s):  
Survival Rate ◽  
Mortality Rate ◽  
Speckle Tracking ◽  
Longitudinal Strain ◽  
Strong Predictor ◽  
Kaplan Meier ◽  
Current Series ◽  
Interstage Mortality ◽  
Stage 1 ◽  
Left Heart Syndrome

Abstract OBJECTIVES The interstage mortality rate after a Norwood stage 1 operation remains 12–20% in current series. In-hospital interstage facilitates escalation of care, possibly improving outcome. METHODS A retrospective study was designed for hypoplastic left heart syndrome (HLHS) and HLHS variants, offering an in-hospital stay after the Norwood operation until the completion of stage 2. Daily and weekly examinations were conducted systematically, including two-dimensional and speckle-tracking echocardiography. Primary end points included aggregate survival until the completion of stage 2 and interstage freedom from escalation of care. Moreover, we calculated the sensitivity and specificity of speckle-tracking echocardiographic myocardial deformation in predicting death/transplant after the Norwood procedure. RESULTS Between 2015 and 2019, 33 neonates with HLHS (24) or HLHS variants (9) underwent Norwood stage 1 (31) or hybrid palliation followed by a comprehensive stage 2 operation (2). Stage 1 Norwood–Sano was preferred in 18 (54.5%) neonates; the classic Norwood with Blalock–Taussig shunt was performed in 13 (39.4%) neonates. The Norwood stage 1 30-day mortality rate was 6.2%. The in-hospital interstage strategy was implemented after Norwood stage 1 with a 3.4% interstage mortality rate. The aggregate Norwood stage 1 and interstage Kaplan–Meier survival rate was 90.6 ± 5.2%. Escalation of care was necessary for 5 (17.2%) patients at 2.5 ± 1.2 months during the interstage for compromising atrial arrhythmias (2), Sano-shunt stenosis (1) and pneumonia requiring a high-frequency oscillator (2); there were no deaths. A bidirectional Glenn (25) or a comprehensive-Norwood stage 2 (2) was completed in 27 patients at 4.7 ± 1.2 months with a 92.6% survival rate. The overall Kaplan–Meier survival rate is 80.9 ± 7.0% at 4.3 years (mean 25.3 ± 15.7 months). An 8.7% Δ longitudinal strain 30 days after Norwood stage 1 had 100% sensitivity and 81% specificity for death/transplant. CONCLUSIONS In-hospital interstage facilitates escalation of care, which seems efficacious in reducing interstage Norwood deaths. A significant reduction of longitudinal strain after Norwood stage 1 is a strong predictor of poor outcome.

scholarly journals Evaluation of chemotherapy response between Paclitaxel-Cisplatin, Paclitaxel -Gemcitabine and Gemcitabine - Cisplatin among non - resectable lung cancer patients, A retrospective study in tertiary care hospital.

2020 ◽  
Vol 38 (4) ◽  
pp. 172-175
Author(s):  
Md Harun Or Rashid ◽  
Quadrat E Elahi ◽  
Md Ashraful Alam ◽  
Fatima Sarker
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Survival Time ◽  
Cancer Patients ◽  
Median Survival ◽  
Median Survival Time ◽  
Chemotherapy Response ◽  
Care Hospital ◽  
Lung Cancer Patients ◽  
Significant Difference

Background: To compare the survival rate of paclitaxel plus cisplatin (PC arm), paclitaxel plus gemcitabine (PG arm) and gemcitabine plus cisplatin (GC arm) in chemotherapy patients with non resectable lung cancer. Methods: This was a retrospective observational study to evaluate chemotherapy response among non resectable lung cancer patients with their survival at cancer center CMH, Dhaka since 01 July 2013 to 31 March 2015. One hundred fifty-four (154) non resectable lung cancer patients were randomly divided into three groups, 50 patients in PC arm, 51 patients in PG arm and 53 patients in GC arm. In PC arm paclitaxel 175 mg/m2 (day 1) with cisplatin 75mg/m2 (day 1), in PG arm Paclitaxel 175 mg/m2 (day 1) with gemcitabine 1000 mg/m2 (days 1 and 8) and in GC arm gemcitabine 1000 mg/m2 (days 1 and 8) with cisplatin 100mg/m2 (day 1). Results: Patients characteristics were similar between the three groups. The overall response rate was 40% in the PC arm,43.1% in the PG arm, 43.4% in the GC arm. The median survival time in PC arm was 8.5 months, in PG arm was 8.8 months, in GC arm was 9.2 months. The major side effect was myelosuppression which accounts 71% patients. The average treatment costs were 57% and 30% lower in PC arm as compared with GC and PG arm respectively. Conclusion: The median survival time, disease free survival time and 1-year survival rate in PC, PG, GC arms without significant difference. Treatment were well tolerable; quality of life parameter was mostly similar but paclitaxel with cisplatin was most cost effective than others chemotherapy regimen. J Bangladesh Coll Phys Surg 2020; 38(4): 172-175

scholarly journals The Dual Effect of CD28 on The Prognosis of Lung Cancer Based On Nomograms: A Comprehensive Analysis of The Tumor Immune Microenvironment

2020 ◽  
Author(s):  
dantong sun ◽  
Lu Tian ◽  
Tiantian Bian ◽  
Han Zhao ◽  
Junyan Tao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Multivariate Analyses ◽  
Cancer Prognosis ◽  
Immune Microenvironment ◽  
Dual Effect ◽  
Internal Validation ◽  
Lung Cancer Patients ◽  
Tumor Immune Microenvironment

Abstract Background Lung cancer has ranked first in China in recent years, and TIME-related molecules may serve as biomarkers for the prognosis of lung cancer. Nomograms are widely used tools for the evaluation of prognosis in malignancies. We performed this study to construct nomograms based on TIME for predicting the prognosis of lung cancer. Methods Univariate and multivariate analyses were performed to estimate prognosis. TIME-related variables and basic clinical characteristics were included in the nomograms. Discrimination and calibration were used for the internal validation of the nomograms. Patients in our center and in the TCGA database were involved in the construction of the nomograms. Results Both LUAD and lung cancer patients with a higher expression of CD28 had a shorter DFS (P = 0.0011; P = 0.0001) but a longer OS (P = 0.0001; P = 0.0282). Nomograms for the DFS of young LUAD patients and the OS of LUAD and lung cancer patients were constructed. The established nomograms provide an easy way to estimate prognosis. Patients may obtain not only probabilities for disease progression and 1-year, 3-year or 5-year survival but also a precise and individualized follow-up regimen. Conclusion TIME-related variables are closely associated with the prognosis of lung cancer patients, especially young LUAD patients. CD28, which has a dual effect on lung cancer prognosis, may be a novel biomarker for not only the prognosis of lung cancer but also sensitivity to immunotherapy. Nomograms based on TIME may be a novel way to predict the prognosis of lung cancer.

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